Dersleri yüzünden oldukça stresli bir ruh haline sikiş hikayeleri bürünüp özel matematik dersinden önce rahatlayabilmek için amatör pornolar kendisini yatak odasına kapatan genç adam telefonundan porno resimleri açtığı porno filmini keyifle seyir ederek yatağını mobil porno okşar ruh dinlendirici olduğunu iddia ettikleri özel sex resim bir masaj salonunda çalışan genç masör hem sağlık hem de huzur sikiş için gelip masaj yaptıracak olan kadını gördüğünde porn nutku tutulur tüm gün boyu seksi lezbiyenleri sikiş dikizleyerek onları en savunmasız anlarında fotoğraflayan azılı erkek lavaboya geçerek fotoğraflara bakıp koca yarağını keyifle okşamaya başlar


Cumulative Effect of Common Genetic Variants Predicts Incident Type2 Diabetes: A Study of 21,183 Subjects from Three Large Prospective Cohorts | OMICS International| Abstract
ISSN: 2161-1165

Epidemiology: Open Access
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
  • Research Article   
  • Epidemiol 2011, Vol 1(3): 108
  • DOI: 10.4172/2161-1165.1000108

Cumulative Effect of Common Genetic Variants Predicts Incident Type2 Diabetes: A Study of 21,183 Subjects from Three Large Prospective Cohorts

Jingyun Yang and Jinying Zhao*
Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, , Oklahoma City, OK 73104, United States
*Corresponding Author : Jinying Zhao MD, PhD,, Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma, HSC, 801 NE 13th Street, Oklahoma City, OK 73104, United States, Tel: 405-271-2229, Fax: 405-271-2068, Email:

Received Date: Sep 26, 2011 / Accepted Date: Nov 05, 2011 / Published Date: Nov 16, 2011


Recent genome-wide association studies (GWAS) and their meta-analyses have identified multiple genetic loci that are associated with type 2 diabetes (T2D). Except for variants in the TCF7L2 gene which had a modest effect on diabetic risk, most genetic variants identified so far have only a weak association with diabetes. It is possible that the combination of multiple variants may have a larger effect on disease risk and improve risk prediction. In this study, we focus on SNPs that had been robustly replicated in previous GWAS and were also genotyped in a large sample of 21,183 participants from three large prospective cohorts, including Atherosclerosis Risk in Communities (ARIC) Study, Framingham Offspring Study (FOS) and Multi-Ethnic Study of Atherosclerosis (MESA). Among these, we were able to successfully confirm the associations of 12 SNPs with baseline prevalent T2D in these two cohorts. A genotype risk score (GRS) using these12 risk variants was constructed to examine whether GRS predicts incident diabetes. In a combined meta-analysis, subjects in the highest tertile of GRS had a 1.62-fold increased risk of incident T2D (95% CI, 1.08-2.44, P=1.5×10-14) compared to those in the lowest tertile of GRS after adjustment for age, sex, race, smoking, body mass index (BMI), lipids (HDL and LDL) and systolic blood pressure. Moreover, GRS significantly improves risk prediction and reclassification in T2D beyond known risk factors.

Keywords: Type 2 diabetes; Single nucleotide polymorphism; Genotype risk score; Incident diabetes.

Citation: Yang J, Zhao J (2011) Cumulative Effect of Common Genetic Variants Predicts Incident Type 2 Diabetes: A Study of 21,183 Subjects from Three Large Prospective Cohorts. Epidemiol 1:108. Doi: 10.4172/2161-1165.1000108

Copyright: © 2011 Yang J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.